CloudQuant Thoughts: We aren’t surprised by JupyterLab winning this award. We are using JupyterLab internally for our researchers. This post was found using a python script running inside a JupyterLab environment that searches for posts that we find interesting and want to share with you.

The Key Factor That Influences The Adoption Of Cloud-Based Machine Learning Platforms

Cloud computing has influenced the rise of machine learning and artificial intelligence. Factors such as affordable storage, availability of GPUs and FPGAs and advancements in deep learning made machine learning accessible and affordable to businesses.

San Diego Workshop Tackles Data ‘Wrangling’ and ‘Cleaning’

Artificial intelligence and machine learning may be the focus of popular and media attention, but data scientists spend most of their time “wrangling” and “cleaning” data so that computers can produce useful information.

A public workshop on Tuesday, Oct. 2, will offer insights into this tedious but fundamental challenge. Thomas Donoghue of UC San Diego’s Department of Cognitive Science will explain the concepts behind data wrangling and cleaning — getting data loaded and checking it for quality.

My Tutorial Book on Anaconda, NumPy and Pandas Is Out: Hands-On Data Analysis with NumPy and Pandas

I announced months ago that one of my video courses, Unpacking NumPy and Pandas, was going to be turned into a book. Today I’m pleased to announce that this book is available!

Hands-On Data Analysis with NumPy and Pandas is now available for purchase from Packt Publishing’s website and from Amazon. This book was created by a team at Packt Publishing who took my video course and turned it into book form. If you’re like me and love books that you …
2018-10-01 00:00:00 Read the full story.

Quality Sleep is an important part of a healthy lifestyle as lack of it can cause a list of issues like a higher risk of cancer and chronic fatigue. This means that having the tools to automatically and easily monitor sleep can be powerful to help people sleep better.

Doctors use a recording of a signal called EEG which measures the electrical activity of the brain using an electrode to understand sleep stages of a patient and make a diagnosis a…
2018-10-01 21:13:36.550000+00:00 Read the full story.

How To Set Up The AI Development Environment For The First Time With Tensorflow

Building algorithmic agents with neural networks is the go-to business strategy in the current technology environment. Now, Google’s Tensorflow library helps developers build these agents with pre-defined functions for easy implementations of various tasks. In this article, we shall be going through the steps to setup an environment for development of these models with Tensorflow library. Setting up an environment for these tasks is mandatory because each model you build is unique to one another and have different dependencies.

movies_df.head() is going to display the first 5 rows of the dataframe. You can pass the number of rows you want to see to the head method. Take a look at the dataframe we’ve got:

Here, I’ve used pandas’ read_csv function which returns a fast and efficient DataFrame object for data manipulation with integrated indexing. I’ve two dataframes from movies_df and credits_df.

Import the python packages which you would need to clean, crunch and visual…
2018-10-02 00:52:42.122000+00:00 Read the full story.

A Chatbot from Future: Building an end-to-end Conversational Assistant with Rasa.ai

A Chatbot from Future: Building an end-to-end Conversational Assistant with Rasa.ai

You might have seen in my previous post that I’ve been using Rasa.ai to build chatbots. You will find many tutorials on Rasa that are using Rasa APIs to build a chatbot. But I haven’t found anything that talks details on those APIs, what are the different API parameters, what do those parameters mean and so on. In this post, I will not only share how to build a c…
2018-10-01 20:55:33.185000+00:00 Read the full story.

Help! I can’t reproduce a machine learning project!

Have you ever sat down with the code and data for an existing machine learning project, trained the same model, checked your results… and found that they were different from the original results?

Not being able to reproduce someone else’s results is super frustrating. Not being able to reproduce your own results is frustrating and embarrassing. And tracking down the exact reason that you aren’t able to reproduce results can take ages; it took me…
2018-09-19 00:00:00 Read the full story.

IPython 7.0, Async REPL – Jupyter Blog

IPython 7.0, Async REPL

Today we are pleased to announce the release of IPython 7.0, the powerful Python interactive shell that goes above and beyond the default Python REPL with advanced tab completion, syntactic coloration, and more. It’s the jupyter kernel for python used by millions of users, hopefully including you. This is the second major release of IPython since we stopped support for Python 2.

This news clip post is produced algorithmically based upon CloudQuant’s list of sites and focus items we find interesting. If you would like to add your blog or website to our search crawler, please email customer_success@cloudquant.com. We welcome all contributors.

This news clip and any CloudQuant comment is for information and illustrative purposes only. It is not, and should not be regarded as “investment advice” or as a “recommendation” regarding a course of action. This information is provided with the understanding that CloudQuant is not acting in a fiduciary or advisory capacity under any contract with you, or any applicable law or regulation. You are responsible to make your own independent decision with respect to any course of action based on the content of this post.

The thoughts and opinions on this site do not represent investment recommendations by CloudQuant or Kershner Trading Group. Securities, charts, illustrations and other information contained herein are provided to assist crowd researchers in their efforts to develop algorithmic trading strategies for backtesting on CloudQuant.